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Integration of SCADA and embedded fuzzy-based load scheduling in Home Energy Management System with grid-connected PV Cover

Integration of SCADA and embedded fuzzy-based load scheduling in Home Energy Management System with grid-connected PV

Open Access
|Apr 2025

Figures & Tables

Figure 1:

Architecture of home appliance scheduling system. FLC, fuzzy logic controller; SCADA, supervisory control and data acquisition.
Architecture of home appliance scheduling system. FLC, fuzzy logic controller; SCADA, supervisory control and data acquisition.

Figure 2:

Hardware configuration of home appliance scheduling system. HMI, human machine interface; MQTT, message queuing telemetry transport; SCADA, supervisory control and data acquisition.
Hardware configuration of home appliance scheduling system. HMI, human machine interface; MQTT, message queuing telemetry transport; SCADA, supervisory control and data acquisition.

Figure 3:

MQTT data communication. AC, air conditioner; FLC, fuzzy logic controller; HMI, human machine interface; MQTT, message queuing telemetry transport.
MQTT data communication. AC, air conditioner; FLC, fuzzy logic controller; HMI, human machine interface; MQTT, message queuing telemetry transport.

Figure 4:

Design of HMI main display. HMI, human machine interface.
Design of HMI main display. HMI, human machine interface.

Figure 5:

Project manager menu of Haiwell Cloud SCADA software. SCADA, supervisory control and data acquisition.
Project manager menu of Haiwell Cloud SCADA software. SCADA, supervisory control and data acquisition.

Figure 6:

Display designer tool of Haiwell Cloud SCADA software. SCADA, supervisory control and data acquisition.
Display designer tool of Haiwell Cloud SCADA software. SCADA, supervisory control and data acquisition.

Figure 7:

Architecture of FLC-based appliance scheduling. FLC, fuzzy logic controller; OM SCH, microwave oven schedule; RC SCH, rice cooker schedule; WH SCH, water heater schedule; WM SCH, washing machine schedule.
Architecture of FLC-based appliance scheduling. FLC, fuzzy logic controller; OM SCH, microwave oven schedule; RC SCH, rice cooker schedule; WH SCH, water heater schedule; WM SCH, washing machine schedule.

Figure 8:

FLC membership function. FLC, fuzzy logic controller.
FLC membership function. FLC, fuzzy logic controller.

Figure 9:

SCADA HMI main display. HMI, human machine interface; SCADA, supervisory control and data acquisition.
SCADA HMI main display. HMI, human machine interface; SCADA, supervisory control and data acquisition.

Figure 10:

SCADA HMI monitoring and control display. HMI, human machine interface; SCADA, supervisory control and data acquisition.
SCADA HMI monitoring and control display. HMI, human machine interface; SCADA, supervisory control and data acquisition.

Figure 11:

SCADA HMI FLC-based appliance scheduling display. FLC, fuzzy logic controller; HMI, human machine interface; OM SCH, microwave oven schedule; RC SCH, rice cooker schedule; SCADA, supervisory control and data acquisition; WH SCH, water heater schedule; WM SCH, washing machine schedule.
SCADA HMI FLC-based appliance scheduling display. FLC, fuzzy logic controller; HMI, human machine interface; OM SCH, microwave oven schedule; RC SCH, rice cooker schedule; SCADA, supervisory control and data acquisition; WH SCH, water heater schedule; WM SCH, washing machine schedule.

Figure 12:

PV power generation and home appliances’ power consumption profiles during a week.
PV power generation and home appliances’ power consumption profiles during a week.

Figure 13:

PV power generation and home appliances’ power consumption profiles in 1 day.
PV power generation and home appliances’ power consumption profiles in 1 day.

Figure 14:

Non-schedulable appliance power consumption profiles during a week.
Non-schedulable appliance power consumption profiles during a week.

Figure 15:

Microwave oven power consumption profiles during a week.
Microwave oven power consumption profiles during a week.

Figure 16:

Microwave oven power consumption profiles in 1 day.
Microwave oven power consumption profiles in 1 day.

Figure 17:

Rice cooker power consumption profiles during a week.
Rice cooker power consumption profiles during a week.

Figure 18:

Rice power consumption profiles in 1 day.
Rice power consumption profiles in 1 day.

Figure 19:

Water heater power consumption profiles during a week.
Water heater power consumption profiles during a week.

Figure 20:

Water heater power consumption profiles in 1 day.
Water heater power consumption profiles in 1 day.

Figure 21:

Washing machine power consumption profiles during a week.
Washing machine power consumption profiles during a week.

Figure 22:

Washing machine power consumption profiles in 1 day.
Washing machine power consumption profiles in 1 day.

Figure 23:

Energy consumption from the grid profile during a week.
Energy consumption from the grid profile during a week.

Comparison of energy consumption from grid during a week

MethodEnergy consumption from grid—Accumulation (watt-hours)
MondayTuesdayWednesdayThursdayFridaySaturdaySundayReduction (%)
Fixed5,323.0511,004.7216,573.0122,108.6427,563.9233,313.9938,815.190
Fuzzy-A5,355.9311,035.5716,611.6522,089.7327,514.7133,190.1138,493.950.8
Fuzzy-B5,311.1310,974.7316,540.0521,800.7427,178.1932,820.4038,102.801.8
Fuzzy-C5,301.7110,626.6516,110.5721,140.7426,438.9431,824.8637,029.844.6

Comparison of daily energy consumption from grid

MethodDaily energy consumption from grid (watt-hours)
MondayTuesdayWednesdayThursdayFridaySaturdaySunday
Fixed5,323.055,681.675,568.305,535.625,455.285,750.075,501.20
Fuzzy-A5,355.935,679.645,576.085,478.095,424.975,675.415,303.84
Fuzzy-B5,311.135,663.615,565.325,260.695,377.455,642.215,282.40
Fuzzy-C5,301.715,324.945,483.925,030.175,298.205,385.925,204.98

Data delivery ratio during real-time simulation

MethodData delivery ratio (%)
Fixed99.60
Fuzzy-A99.61
Fuzzy-B99.56
Fuzzy-C99.70
Average99.62

Some fuzzy rules in the second scenario (Fuzzy-B)

No.PV Power H8PV Power H12PV Power H15WeekdayRC SCHWH SCH1WM SCHOM SCHWH SCH2
1LowLowLowWork78121415
2LowLowLowOff89121415
3LowLowMedWork78121516
4LowLowMedOff89121516
21MedHighLowWork67101415
22MedHighLowOff78101415
23MedHighMedWork67101516
24MedHighMedOff78101516

Some fuzzy rules in the first scenario (Fuzzy-A)

No.PV Power H8PV Power H12PV Power H15WeekdayRC SCHWH SCH1WM SCHOM SCHWH SCH2
1LowLowLowWork67121517
2LowLowLowOff89121415
3LowLowMedWork67121517
4LowLowMedOff89121516
21MedHighLowWork67101517
22MedHighLowOff78101415
23MedHighMedWork67101517
24MedHighMedOff78101516

Some fuzzy rules in the third scenario (Fuzzy-C)

No.PV Power H8PV Power H12PV Power H15WeekdayRC SCHWH SCH1WM SCHOM SCHWH SCH2
1LowLowLowWork910121314
2LowLowLowOff910121314
3LowLowMedWork910121415
4LowLowMedOff910121415
21MedHighLowWork89111314
22MedHighLowOff89111314
23MedHighMedWork89111415
24MedHighMedOff89111415
Language: English
Submitted on: Sep 15, 2024
Published on: Apr 27, 2025
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year

© 2025 Sugeng Priyanto, Aryuanto Soetedjo, Irrine Budi Sulistiawati, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.